class_docstr: Construct a CoreML KNearestNeighborsClassifier specification.
  
  Please see the Core ML Nearest Neighbors protobuf message for more information
  on KNearestNeighborsClassifier parameters.
  
  Examples
  --------
  .. sourcecode:: python
  
      from coremltools.models.nearest_neighbors import KNearestNeighborsClassifierBuilder
      from coremltools.models.utils import save_spec
  
      # Create a KNearestNeighborsClassifier model that takes 4-dimensional input data and outputs a string label.
      >>> builder = KNearestNeighborsClassifierBuilder(input_name='input',
      ...                                              output_name='output',
      ...                                              number_of_dimensions=4,
      ...                                              default_class_label='default_label')
  
      # save the spec by the builder
      >>> save_spec(builder.spec, 'knnclassifier.mlmodel')
      
docstr: Set the index type for the KNearestNeighborsClassifier model.
  
  Parameters
  ----------
  index_type
          One of [ ``'linear'``, ``'kd_tree'`` ].
  
  leaf_size
          For kd_tree indexes, the leaf size to use (default = 30).
  
  Returns
  -------
  None
docstr_tok: ["Set","the","index","type","for","the","KNearestNeighborsClassifier","model",".","Parameters","--","--","--","--","--","index_type","One","of","[","``","'linear","'","``",",","``","'kd_tree","'","``","]",".","leaf_size","For","kd_tree","indexes",",","the","leaf","size","to","use","(","default","=","30",")",".","Returns","--","--","--","-","None"]
code: def set_index_type(self, index_type, leaf_size=30):
      """
      Set the index type for the KNearestNeighborsClassifier model.
  
      Parameters
      ----------
      index_type
              One of [ ``'linear'``, ``'kd_tree'`` ].
  
      leaf_size
              For kd_tree indexes, the leaf size to use (default = 30).
  
      Returns
      -------
      None
      """
      index_type = index_type.lower()
      if index_type not in self._VALID_INDEX_TYPES:
          raise TypeError("Invalid index type")
  
      if index_type == "kd_tree":
          if leaf_size <= 0:
              raise TypeError("leaf_size must be > 0")
          self.spec.kNearestNeighborsClassifier.nearestNeighborsIndex.singleKdTreeIndex.leafSize = (
              leaf_size
          )
      else:
          self.spec.kNearestNeighborsClassifier.nearestNeighborsIndex.linearIndex.MergeFromString(
              b""
          )
  
      # storing this in the object is just a convenience
      self._index_type = index_type
  
imports: import numpy
  import coremltools
  from ...proto import FeatureTypes_pb2
  from ..None import datatypes
label_desc: Use image node_id 13 for calling the KNearestNeighborsClassifierBuilder obj's underlying member method code with example usage: obj.set_index_type(index_type, leaf_size) without return types